The present invention relates to an apparatus and method for controlling a plant.
Several techniques for controlling an object modeled using a model parameter (such an object is also called a plant) have been proposed. Considering disturbance that may be applied to the plant, an estimated value of the disturbance (which will be hereinafter referred to as an estimated disturbance value) can be included in the model expression for the plant.
According to a control technique described in Japanese Patent Application Publication No. 2003-5804, reference values for the model parameters, including the above estimated disturbance value, are scheduled in accordance with an engine condition parameter (for example, a throttle valve opening) that is in a correlation with the model parameters. An identifier, which is introduced in a control apparatus, recursively identifies the model parameters and the estimated disturbance value based on the scheduled model parameters. A control input into the plant is calculated based on the identified model parameters and estimated disturbance value. Such a control technique has an advantage that the model parameters can be caused to converge to their optimum values while minimizing a delay even when the engine condition parameter changes.
Depending on the type of the plant, some model parameters need to be changed by a relative large amount so as to cause an actual output of the plant to appropriately converge to a desired value when the engine condition parameter changes. The estimated disturbance value may largely vary due to such a large change of the model parameters.
For example, in the case where the model parameters and the estimated disturbance value are recursively identified, the estimated disturbance value may largely change due to changes of the model parameters if the identification speed for the model parameters is different from the identification speed for the estimated disturbance value. Further, in the case where model parameters are recursively identified based on the scheduled parameters, the estimated disturbance value may largely change if the values of the scheduled parameters change in accordance with a change of the engine condition parameter.
Such a large change of the estimated disturbance value may change a term associated with the estimated disturbance value in the control input equation. As a result, a steady state error may occur between an output of the model and an actual output of the plant. In order to suppress such a steady state error, the amount of change of the model parameters needs to be minimized. However, such minimization may impair the above-described advantages.
Therefore, there is a need for a control that can suppress such a steady state error that may be caused by change of an estimated disturbance value while minimizing the time required for causing model parameters to converge to their optimum values.